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O C C A S I O N A L PA P E R S E R IN O 7 7 / D E C E M B E R2 0 0 7

OIL MARKET STRUCTURE,

NETWORK EFFECTS AND

THE CHOICE OF CURRENCY

FOR OIL INVOICING

byElitza Mileva andNikolaus Siegf ried



In 2007 all ECB publications

feature a motif taken from the €20 banknote.

OCCASIONAL PAPER SERIESNO 77 / dECEmbER 2007

by Elitza Milevaand Nikolaus Siegfried1

OIL mARKET STRUCTURE,NETWORK EFFECTS

ANd THE CHOICE OF CURRENCYFOR OIL INVOICING

This paper can be downloaded without charge fromhttp://www.ecb.europa.eu or from the Social Science Research Network

electronic library at http://ssrn.com/abstract_id=1005940.

1 Fordham University, New York, and Thames River Capital, London, respectively. The paper was written while the rst author was an intern in the European Central Bank’s DG-International and European Relations and the second author

was an economist in the same DG. Nikolaus Siegfried, tel.: +44 7 814 735 547 : Elitza Mileva, 441 East Fordham Road, Bronx,New York 10458, United States; tel.: +1 917 957 9361; e-mail: [email protected].



© European Central Bank 2007

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The views expressed in this paper do not necessarily re ect those of the EuropeanCentral Bank.

ISSN 1607-1484 (pr int)ISSN 1725-6534 (online)



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Occasional Paper No 77December 2007

CONTENTSCONTENTS

AbSTRACT 4

SUmmARY 5

1 INTROdUCTION 6

2. THEORETICAL LITERATURE ON THE USEOF CURRENCIES IN INTERNATIONAL TRAdE 7

3 THE OIL mARKET 9

3.1 Overview of supply 93.2 The demand for oil 103.3 World oil trade ows 113.4 The spot, term and futures

markets 12

4 CHOOSING A CURRENCY FOR OILINVOICING – THE ROLE OF NETWORKEFFECTS 15

4.1 Network effects in the use of money 15

4.2 A model for oil invoicing 154.3 Steady states and the adoption

curve 174.4 Sensitivity analysis for the model

parameters 17

5 CONCLUSION 20

REFERENCES 21

APPENdIX

WORLd CRUdE OIL TRAdE FLOWS 24



4EC BOccasional Paper No 77December 2007

AbSTRACT

A recurring theme in recent years in the debateon the international role of currencies has

been the possiblity of pricing oil in euro. This paper contributes to these debates by providinga detailed review of the empirical evidenceregarding the market for crude oil and currentoil invoicing practices. It introduces a network effect model to identify the conditions under which a parallel invoicing in different currencieswould be possible. The paper also includes asimulation designed to illustrate the dynamicsof the currency choice of oil invoicing.

JEL Classi cation: G14, O13, Q41

Keywords: trade invoicing, currency substitution,network effects, oil trade.



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SUmmARYSUmmARY

The traditional economic literature providesample reasons why oil is invoiced in onesingle currency around the globe. Speci callythe literature on trade invoicing underscoresthe critical characteristics of crude oil as ahomogeneous good traded on specialisedexchanges and quoted and invoiced

predominantly in one currency, the US dollar.In addition, a number of features of the USeconomy – macroeconomic stability, deep

nancial markets and global trade power – facilitate the use of the US dollar to provide astore of value and price transparency in the oilmarket.

Despite the strong case for the use of one vehiclecurrency in the oil trade, the analysis of this

paper suggests that the introduction of a newcurrency in the crude oil market is possible. Our detailed survey of the oil market reveals that,

contrary to the suggested homogeneity of thecrude oil market, the international oil trade is

predominantly regional in nature. For example, theUnited States, the biggest importer of petroleum,

purchases oil mainly from countries in thewestern hemisphere. This market segmentationis due primarily to the speci c features of theoil industry. Geographical proximity, for one,translates into lower transportation costs. Second,it is very costly to adapt re neries processinglight oil in order to switch to a heavy grade.A closer look at the overall trade patterns of theoil exporting countries shows that the out ow of crude oil from most of these nations is matched

by an in ow of other goods and services fromtheir trading partners. This nding prompts thequestion of whether it would be more ef cientfor oil producers to invoice their exports in thecurrency they use to pay for their imports.

In addition to the review of physical oil trading,this paper examines the markets for oil spot andfutures contracts. These markets are dominated

by two commodity exchanges – NYMEXin New York and IPE in London – and the

benchmark grades traded there are commonlyused to price various other grades of oil.

However, developments in some markets havecontributed further to the segmentation of thecrude oil market. India and Japan, for example,have introduced the trading of futures contractsfor petroleum grades more relevant to localindustry. These are denominated in domesticcurrency. Trading oil futures contracts indifferent currencies will lower and eventuallyeliminate the cost of quoting, comparing pricesand invoicing physical crude oil contracts incurrencies other than the US dollar.

To explain the dominant use of one currency inoil invoicing, and to show that the use of severalcurrencies is possible, we sketch a model thatis based on the theory of network effects,i.e. we treat cur rencies as network goods. Sellersin the market respond to the currency choices of

buyers so as to minimise costs associated withthe use of an established vehicle currency or anewly introduced currency. We calibrate themodel using low actual values (to the tune of

4 basis points) for the transaction costs of usingone or two currencies, as well as a proxy for information costs, which decline with the useof a new currency. The results show that therewill be a switch to parallel invoicing in bothcurrencies when two conditions are met: rst,oil exporters expect that a certain minimumnumber of other oil exporters will also startusing the new currency; and second, theinformation costs associated with quoting oilcontracts in two currencies are low.




1 INTROdUCTION1

A recurring theme in recent years in thedebate on the international role of currencieshas been the possibility of pricing oil in euro.Discussions have taken place in the media(Islam, 2003), academia (Alhajji, 2005) theEuropean Parliament (2004) and OPEC (Koch,2004).

The literature on trade invoicing suggests that primary commodities, such as crude oil, tendto be priced in vehicle currencies, becausethey are homogeneous and prices are easilycomparable. Petroleum has mostly been tradedin US dollars since the Seneca Oil Companydrilled the rst oil well in Pennsylvania in1859. There are only a few exceptions to thisstatement. In the 1940s Anglo-Iranian (nowknown as BP) concluded some large crude oilcontracts with Standard Oil of New Jersey andStandard Oil of New York (now ExxonMobil)

in pounds sterling (Bamberg, 2000). A secondcase in point is the 1950s sterling-dollar oilcontroversy, in which the British governmentestablished exchange controls on oil importsand required the pricing of petroleum in poundssterling in order to stop a short-term dollar drain(Schenk, 1996). A third example is the practicesof the countries of the Persian Gulf which were

part of the sterling area, which quoted their oil prices in US dollars but accepted payment in pounds sterling (McKinnon, 1979, p. 77). Morerecently, in October 2000 the Iraqi governmentdemanded the settlement of its pet roleum exportsin euro under the UN Oil-for-Food Programme(CNN, 2000). In addition to these four instances,when actual settlement of the internationaloil trade occurred in pounds sterling or euro,there is also the case of crude oil exports to theUnited States being priced in Canadian dollars

but settled in US dollars, so that the producers bear the exchange rate risk. Finally, Chinese oilcompanies – such as the two largest, CNOOC Ltdand Petrochina Company Ltd – price their locally produced crude oil in US dollars on the

basis of international benchmark grades, but

settle domestic contracts (the majority of their crude oil sales) entirely in renminbi. While these

are, admittedly, just exceptions, the examplescited above have prompted the present study of the oil market and the possibility of invoicingand settling oil trades in a currency other thanthe US dollar.

This paper reviews in detail the empiricalevidence regarding the crude oil marketand current oil invoicing/settling practicesand develops a network effect-based modelde ning the conditions under which acomplete switch in the oil invoicing currencyor parallel invoicing in different currencieswould be possible. This paper is in ve parts.The following section discusses the literatureon currency use in international trade.Section 3 explores the oil market in some detail.Section 4 considers network effects in the use of money and, on the basis of these considerations,

presents a small theoretical model and somesimulations for illustration. The last sectionconcludes.

This paper has profited considerably from a number of helpful1suggestions and comments. We would like to thank AdalbertWinkler, Domiciano Calvo Garcia, Francesco Mazzaferro,

Michael Sturm, Oscar Calvo-Gonzalez and Troy Tassier for their contributions. The views expressed in this paper aresolely those of the authors.



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2 THEORETICALLITERATURE ON THE

USE OF CURRENCIES ININTERNATIONAL TRAdE

2 THEORETICAL LITERATURE ON THE USE OFCURRENCIES IN INTERNATIONAL TRAdE

This section provides an overview of thetheoretical explanations for the choice of invoicingcurrency in trade, re ecting the three functions of money: medium of exchange, unit of account andstore of value. 2 Note that the terms invoicing and

settlement are used throughout this paper inrelation to the medium of exchange function of money, as is standard practice in the literature.The important issue here is who bears theexchange rate risk – the buyer or the seller. Adistinction is made, however, between the mediumof exchange function and the unit of accountfunction, with the term quotation used in this

paper in relation to the latter.

Most theoretical literature on trade invoicingfocuses on money as a medium of exchange anddiscusses the role of vehicle currencies in thetrading of goods or the exchange of currencies.

Swoboda (1968) argues that, if residents of acountry may only hold non-interest bearingforeign currency assets, and their revenues or expenditures are at least partly denominated in aforeign cur rency, it is, owing to transaction costs(e.g. brokers’ fees, bookkeeping, psychologicalinconvenience, etc.), pro table for them tohold foreign currency cash balances. Krugman(1980) develops a formal three-country,three-currency model, in which transactioncosts as a proportion of the transaction sizedecline as the size of the exchange marketincreases. He shows that only the currency of an economically dominant country can serve asa vehicle currency. Moreover, once a currencyis established as an international mediumof exchange, its vehicle role becomes self-reinforcing and may persist even if the country’seconomic power diminishes. Krugman’s staticanalysis also allows for multiple equilibria withmore than one vehicle currency in international

payments at any one time. Extending Krugman’smodel, Rey (2001) integrates internationalgoods and currency exchange and suggests thatthe “thick market” externality (i.e. economies

of scale in foreign exchange markets) and trade parameters such as the degree of openness, the

level of integration between the countries or transportation technologies are the key variableswhich characterise these multiple steady stateequilibria and have an impact on the choice of vehicle currency.

Invoicing decisions in international tradeare also modelled and tested empirically byGoldberg and Tille (2005). They contrast factorsthat in uence the choice of currency and ndthat industry characteristics, such as the degreeof product differentiation, are more importantthan macroeconomic factors such as exchangerate volatility. Their analysis presents evidencethat the vehicle role of the US dollar is explained

by both the importance of transactions ingoods traded in organised exchanges and thesigni cant role played by the United States asan international trade partner.

A different branch of the vehicle currencyliterature assumes positive network externalities

in the use of money. Section 4.1 of this paper deals in greater detail with the theory of network effects for the use of currencies.

The theoretical literature on the secondrole of money, as a unit of account , is notwell developed. It is often assumed that thequotation currency is the same as the invoicingor settlement currency and the theory of vehiclecurrencies is applied. McKinnon (1979) treatsmoney as a medium of exchange but reachesan important conclusion regarding the unitof account function. McKinnon suggests thatthe use of vehicle currencies in the tradingof homogeneous goods such as primarycommodities is dictated by the need for pricetransparency. He also argued that trade onBritain’s commodity exchanges had continuedto be conducted in pounds sterling, despitesterling’s relative decline (at that time) as avehicle currency, because of the long historyof such currency use and the familiarity withthe pound of merchants involved in theseexchanges.

For a detailed survey of the theoretical literature on the topic,2 including vehicle currencies in foreign exchange markets,see Har tmann (1998, pp. 11-29).




Thirdly, investment currencies ful l the purpose of international money as a store of value .3 The general result of international asset

pricing models is that ef cient portfolios areusually well diversi ed across many currencies

because of risk-reducing considerations, whichis in contrast to the predictions of the mediumof exchange theory that there may be only alimited number of vehicle currencies. However,considerable currency diversi cation in

nancial portfolios is not actually observed.This may occur, because the store of value andmedium of exchange functions of money areinterrelated. On the one hand, countriesimportant in international trade tend to havedeep nancial markets and no capital controls,and therefore they attract foreign investors. Onthe other hand, countries with large andsophisticated nancial markets experience highdemand for their currencies for internationaltrade payments (Har tmann, 1998, p. 28).

To explain the role of money as a store of value,Giovannini and Turtelboom (1994) use a cash-in-advance-constrained model and incorporatethe costs incurred in instantly transforming

nancial assets into cash for use in purchasinggoods. The demand for domestic or foreigncurrencies is determined by their expected“liquidity services”. Thus, in countries withunderdeveloped nancial markets (i.e. nancialassets are illiquid), the liquidity services of money are signi cant and, if the domesticcurrency provides low expected returns (asis the case in high in ation countries), theforeign currency becomes an attractive liquidinvestment.

The analyses in many of the studies reviewedabove apply to the trading of crude oil asa homogeneous good traded in organisedexchanges (though only recently and mostlyspeculatively) and denominated in the currencyof the country which dominates internationaltrade. However, as the discussion of the oilmarket in the following section suggests,multiple currency invoicing in this particular

industry might prove to be more likely than has previously been assumed.

The concept of money as a store of value is ambiguous in3the literature. McKinnon (1985), for example, differentiates

between direct and indirect currency substitution , the former referring to the competition between currencies to serve asa means of payment, the latter to switching between non-monetary nancial assets. Giovannini and Turtelboom (1994)attempt to clarify this issue. In their model, direct is thesubstitution of currencies and indirect is the substitution of

bonds. In the interests of simplicity and for practical reasons,this paper focuses only on the monetary aspect (i.e. direct currency substitution).



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3 THE OIL mARKET

3 THE OIL mARKET

The most widely accepted theoreticalapproach to the economics of oil focuses onthe prevailing oligopolistic market. Accordingto Adelman (1993), the long-term marginalcost is a small fraction of the price of oil, evenwhen making considerable allowances for thefuture values of the resources used up today(“user costs”). To support high price levels,the excess supply is restricted by a cartel. Themarket works in the following way: higher-cost producers sell all they can produce, whilelow-cost producers satisfy the remainder of the demand at current prices and cut back

production if needed. Econometric evidenceon Saudi Arabia con rms the asymmetric

behaviour of the low-cost petroleum suppliers:the country restricts production in reaction tonegative demand shocks but does not expand

production in response to positive ones, inorder to sustain high prices (De Santis, 2000).

The oligopolistic structure of the oil market or the dominant role of Saudi Arabia is supportedin a number of other empirical studies(cf. Grif n, 1985; Alhajji and Huettner, 2000;and Dees et al., 2003).

3.1 OVERVIEW OF SUPPLY

The power of the producing countries is,in general, rooted in the characteristics of oil. Producers incur no storage costs, since

petroleum is simply left in the ground, whileconsuming countries have to cover thetechnical costs of building storage facilities,interest on the value of oil stocks and variousrisks (e.g. environmental risks). In addition,oil production is not labour intensive and,therefore, the oil supply can be controlled easily

by reducing depletion rates without affectingthe labour market. Since there are no short-term substitutes for petroleum, changes insupply are also effective. Moreover, demand for crude oil is highly insensitive to price changes(cf. Cooper, 2003).

The most important player in the oil market – the Organization of the Petroleum Exporting

Countries (OPEC), founded in 1960 inBaghdad – comprises a diverse group of developing nations, 4 highly dependent on oilexports and uni ed by their common interestin oil revenue maximisation. On average,

petroleum exports represent over 68% of thetotal exports of these countries. Aiming tosustain world demand for oil (as opposed toreplacing it with alternative energy sources),OPEC has to balance market share and pro ts.The oil cartel’s market power comes from thesheer size of its proven oil reserves (891 billion

barrels) and exports (19.5 million barrels per day) – 78.3% and 48.7% respectively of the2003 worldwide totals (OPEC, 2003). The Gulf countries also have the lowest production costs:USD 4.00 per barrel for Saudi Arabia or USD 4.50 for Iran, as compared, for example,with USD 9.85 for the North Sea and USD 12.50for Brazil (Energy Intelligence, 2004). Inaddition, most OPEC oil is produced by 100%state-owned companies (as is the case in

Algeria, Iran, Kuwait, Qatar, Saudi Arabia andVenezuela) or majority state-owned companies(Libya, Nigeria and United Arab Emirates).Only in Indonesia is government participationin the oil sector very limited.

The country with the largest weight amongthe oil exporting nations is Saudi Arabia.It has the world’s largest proven petroleumreserves (one-quarter of the total) and some of the lowest production costs, and is the largest

producer and net exporter of oil (see Appendix,Table 1). As of May 2005, owing to the recentrapid increase in demand for petroleum, SaudiArabia is the only country with any surplus

production capacity: 900-1,400 thousand barrels per day, or some 13% of total capacity(EIA, 2005b). This enormous capacity hasallowed Saudi Arabia to play the role of “swing”

producer.

The non-OPEC exporting countries, on theother hand, increased their international oilmarket share following the 1973-74 oil crisis,

Algeria, Indonesia, Iran, Iraq, Kuwait, Libya, Nigeria, Qatar,4Saudi Arabia, United Arab Emirates and Venezuela. Angola

joined OPEC only in 2007.




at the expense of OPEC. By contrast with theMiddle Eastern countries, their oil productionis characterised by technological dif culties(e.g. the North Sea) and high transportationcosts (e.g. Alaska). The development of theseoil reserves contributes to the geographicaldispersion of petroleum production and theincreased energy independence of somecountries. While this would in principle implya decline in international trade in crude oil,no signi cant decrease has yet been observed.Because of the different qualities of crudeoil, it is more economical for some countries,whose re neries have not been adapted to

process the newly discovered petroleum, toexport their own grade of oil and to import thequality suitable for re ning at home. Owing tothe difference in construction materials used(related mainly to the qual ity of steel), the costof building a re nery which processes heavycrude oil, for instance, can be six times that of are nery with the same capacity built to process

light grades of petroleum. A good example of oil trading conducted for petroleum qualityreasons is the United Kingdom, which in2003 exported 1,345 thousand barrels per daywhile importing 968 thousand barrels per day(see Appendix, Tables 1 + 2). Because NorthSea oil is of a high quality, it is more suitablefor processing at US re neries. Similarly, asis the case in Alaska, national oil elds may

be located a long way from re neries andconsumption locations and it may, therefore,

be better to export the petroleum they produce(e.g. to Japan). In the end, these qualityconsiderations contribute to the segmentationof the oil market.

In addition to the producing countries discussedabove, the oil market includes both major oilcompanies and various smaller rms. Theformer are ve very large, vertically integratedmultinational corporations: British Petroleum(BP), ExxonMobil, Total, Royal Dutch/Shelland ChevronTexaco. Together, these produce15.6% of the total annual world petroleum output(OPEC, 2003). Three of these companies have

headquarters in the EU and account for their pro ts in euro or pounds sterling and use nancial

instruments to hedge against exchange rate risk. 5 The two American corporations also report someuse of foreign currency derivatives. The smaller oilcompanies (the “independents”) tend to operate inonly one of the oil sector’s technically segmented

productive stages or to rely on a single country or region for their oil supplies.

3.2 THE dEmANd FOR OIL

Unlike supply, demand for crude oil depends onthe choices of many individual households and

rms. However, owing to its importance for theeconomy and national security, the demand sideis in uenced by various pr ivate interest groups,the most in uential of which being domestic oilre ners without foreign supply sources andgovernments, whose aim is to acquire suf cientquantities of petroleum from stable sources. Oilimporting governments in uence the pet roleummarket by means of scal instruments, anti-trust policies, public funds for alternative

energy research or petroleum explorationactivities, political intervention in situations inwhich the interests of the nation are at stake, 6 environmental regulations 7 and strategic oilreserves. 8

In addition to policy measures, governments insome oil importing countries, such as China,South Korea, Singapore, Taiwan, Thailand,Turkey and Brazil, own majority stakes in their countries’ main oil companies. Nevertheless,the tendency over the last decade has been to

privatise and deregulate the energy sector. As a

In 2004, for example, Royal Dutch/Shell reported foreign5exchange contracts, swaps and options worth USD 18.8 billion,while Total reported instruments with a value of € 116 million(notional amounts; 2004 annual reports).One example is the political controversy which surrounded6the cancellation of the bid by the state-owned China

National Offshore Oil Company (CNOOC) to buy Unocal,the California-based ninth largest US petroleum corporation(Barboza and Sorkin, 2005).For instance, the Kyoto Protocol, which was negotiated in 19977and has, to date, been rati ed by 141 countries.Some countries, such as the United States and Japan, hold8segregated petroleum stocks. These totalled nearly 1.38 billion

barrels in 2003. Elsewhere (e.g. in the EU), oil companies arerequired to hold a minimum level of extra stocks – currently90 days’ worth of consumption (Energy Intelligence, 2004).



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3 THE OIL mARKET

Ta le 1 Tra e volu e y co o ity exchange, 2003

Exchange Futures contract Thousand barrels

NYMEX Light, Sweet Crude Oil 45,436,931e-miNY sm Light, Sweet Crude Oil 138,706

IPE Brent Crude 24,012,969TOCOM Crude Oil (Middle East Crude) 1,138,308Total world production 24,487,850

MCX India (Feb.-Dec. 2005) Crude Oil (Light, Sweet Crude) 512,828

Sources: NYMEX, IPE, TOCOM, MCX and OPEC.

over 50% of global trade in crude oil: SaudiArabia, Kuwait, Qatar, Oman and Libya sell

predominantly using contracts; Russia and Nigeria mainly use spot markets; and Norway,Mexico and Venezuela actually split their salesin line with the global average shares for thedifferent types of selling price (EnergyIntelligence, 2004).

Spot deals, on the other hand, are de ned asimmediate deliveries of crude oil outside of any continuing supply commitment. Althoughthe spot market accounts for less than 50% of

physical oil sales, spot prices are the primarydeterminant of almost all other petroleum

prices. They are, for example, used in most pricing formulae for the term crude oil salesof OPEC and many other producing countries(Energy Intelligence, 2004).

Despite its signi cance, the spot market isnot fully transparent (in terms of both prices

and quantities), since physical spot markettransactions have no central clearing house andare often con dential. Platts, the world’s leading

pricing service, which is quoted by Bloombergand Reuters, bases its daily evaluations of 62 grades of crude oil on the prices of petroleumshipments from the main transportation hubs(maritime terminals or pipeline centres) under typical market conditions. This implies thatPlatts’ oil price assessment methodologies differ depending on the characteristics of the marketfor a particular grade. Trade deals in the variousoil regions differ in terms of pricing (e.g. pricesof cargoes loaded free on board (FOB), delivered

prices net of freight costs (CIF), or prices posted by re ners), cargo size, timing of delivery and so

on. To add to the complexity and segmentation of the market, the posted prices for some Canadiangrades, such as Light Sour Blend and Par Crude,are quoted in Canadian dollars, although allother (non-Canadian) grades are priced inUS dollars. Since 14 February 2005 Platts hasalso reported certain benchmark grades – suchas Dated Brent, Urals and WTI – in euro as asupplement in order to allow price comparisonacross regions (Platts, 2005).

The other recent development in the oil industryis the growing in uence of the market for futures contracts. In 1983 the New York Mercantile Exchange (NYMEX) introduced the

rst crude oil futures contract, Light, SweetCrude Oil, the most actively traded commodityderivative today. In 1988 the InternationalPetroleum Exchange (IPE) 13 in London startedtrading in Brent Crude futures. Data for 2003suggest that, collectively, the annual trade of the two commodity exchanges is nearly three

times the actual volume of physical oil produced(see Table 1).

In September 2001 the Tokyo CommodityExchange (TOCOM) also listed a crude oilfutures contract based on a benchmark Asiangrade of petroleum – Middle East Crude Oil. Inspite of its relatively low volume by comparisonwith those traded in New York and London,and despite its cash settlement requirement, theemergence of this futures contract is important,

In 2001 the IPE was acquired by the Intercontinental Exchange13 (ICE), a conglomerate of major banks and oil companieswhose ambition is to establish a platform for the trading of all

physical, forward, futures, and over-the-counter derivativesfor all commodities (Energy Intelligence, 2004).



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4 CHOOSINGA CURRENCY FOR OIL

INVOICING – THE ROLEOF NETWORK EFFECTS

4 CHOOSING A CURRENCY FOR OILINVOICING – THE ROLE OF NETWORKEFFECTS

4.1 NETWORK EFFECTS IN THE USE OF mONEY

Network effects arise when the utility aconsumer derives from a particular good isdependent upon the number of other individualsalso consuming that good (Katz and Shapiro,1985). The network property of a good has thefollowing four implications for the market for that good. First, a minimum level of agentsusing the good ( critical mass ) is necessary for the initial adoption of a network good (Farrelland Saloner, 1986). Second, the demand for network commodities is associated with abandwagon effect , i.e. the more individualsuse the good, the more incentive there will befor other individuals to use it as well. Third,network effects may give rise to multiple and unstable equilibria related to the interplay of

information, expectations and coordination(Stenkula, 2003). Finally, there are two problemslinked to network goods, which may result inmarket failures : excess inertia, i.e. resistance

by individuals to using a “superior” network commodity, and excess momentum, i.e. a rush

by individuals to an “inferior” network good(Farrell and Saloner, 1985 and 1986).

Treating money as a network good is a recentdevelopment in economics and has led tointeresting results concerning the origin of money, at currency and monetary integration.In a series of papers Kiyotaki and Wright(1989, 1990 and 1993) formalise the idea thatindividuals use a at currency to avoid thenecessity of “the double coincidence of wants”and, based on a search-theoretic model, show thatmultiple currencies may coexist in equilibrium.The transition from commodity money (throughconvertible currencies) to at money is discussed

by Dowd (2001). He argues that governmentintervention is needed to support a particular atcurrency, since network effects may also work against the establishment of at money. Selgin

(2003) takes the search models a step further byintroducing adaptive learning in the transition to

at money. Lotz and Rocheteau (2002) emphasisethe role of the government in forcing a switchfrom one at currency to another.

4.2 A mOdEL FOR OIL INVOICING

This section develops a model that capturesnetwork effects in the oil market, extendingthe models developed by Stenkula (2003) andOomes (2003). The market consists of many

buyers ( B) and sellers ( S ) of crude oil . While theoil producers are sellers in this game, they havean incentive to invoice their oil contracts in thecurrency with which they will pay for their (non-oil) imports of goods and services f rom the restof the world. In short, we will call these (non-oil) goods and services food . Similarly, the restof the world are buyers of oil and sellers of food.Both parties aim to minimise foreign exchangerisk and costs associated with the use of aspeci c currency for trade. In an environmentwhere buyers and sellers are matched randomly

and are subject to cash-in-advance constraints, both types of agents may choose between twocurrencies, i.e. euro ( e) or US dollars ( d ), as theinvoicing currency for their contracts. Eachcontract is fully invoiced in a single currency. Inaddition, the price of each contract is assumedto be constant and normalised to one. At time t ,the sellers sell oil to the buyers, while at timet + 1 , the buyers of oil sell food to the oil sellers.Hence, all agents try to anticipate the currencythey will need for purchases in the next period.

Depending on whether or not the currency theyaccept for payment for oil is the same as thecurrency they use for their imports, the oil

producers (S ) may incur three types of cost,related to the three functions of money – mediumof exchange, unit of account and store of value. 14

Transaction costs ( τ ) are associated with theexchange of one currency for another or hedgingagainst exchange rate risk in the event that oil

producers export and import in different

Note that, although for the remainder of the paper we refer 14to oil exporting countries, the analysis for oil companies is

similar: they are either buyers or sellers of oil, or both; andthey too incur costs when they invoice oil in one currency andhave to record pro ts and pay taxes and dividends in another.




currencies. Second, they incur information costs – i(p t ) – when quoting and comparing oil prices inthe presence of a new vehicle currency. Since theUS dollar is the historically established invoicingcurrency in the oil trade, i.e. the currencyeveryone is used to dealing with, participantsmust learn to use a new unit of account.Information costs decline exponentially over time, accounting for the learning curve effects(or experience curve effects)

i(p t ) = A exp (-α p t ),

where t is discrete time; p t is the share of oil producers that invoice their contracts in euroand, equivalently, the probability that a seller will invoice a crude oil contract in euro; A is thevalue at p t = 0 ; and α is a positive constant (rateof decay). Finally, oil producers incur liquiditycosts , i.e. the opportunity cost of holdingcash balances owing to the loss of purchasing

power between periods t and t + 1 . However, the

liquidity costs do not depend on the invoicingcurrency. Consider the following example: if acountry sells oil in US dollars at time t to buyfood in euro at time t + 1 and the opportunitycost of holding US dollars is higher than thatof holding euro, it is optimal for the countryto exchange US dollars for euro at time t .Therefore, for the sake of simplicity, we haveexcluded liquidity costs from our model.

Table 2 shows the cost matrix for the oil producers.The sellers incur no costs if they invoice oil exportsin US dollars (line S(d)) and pay for their importsin the same currency (column B(d), i.e. the buyers

prefer dollars). They have to cover transactioncosts if exports are settled in US dollars butimports are paid for in euro. When the euro isused for invoicing oil and the US dollar is used for importing food, both transaction and information

costs are incurred by the oil producers. Finally,when the euro is the settlement currency of bothexports and imports, the oil producers have tocover information costs.

Since the oil exporters’ willingness to accept agiven currency for their crude oil sales dependson the currency they use for their purchases of food, we de ne ˆ p t + 1 as the expected share of imports of food invoiced in euro at time t + 1 .Thus, a representative seller’s expected costfunctions – C (d ) and C (e) – for invoicing its oilcontracts in US dollars or euro respectively areas follows:

C (d ) = ˆ p t + 1 τ + εd t

C (e) = (1 – ˆ p t + 1 ) [τ + i( p t )] + ˆ p t + 1 [i( p t )] + εet

The last variables on the right-hand side of theabove equations, εd

t and ε et , represent other

random costs, which are not explained by

network effects and which are speci c to eachseller. These costs may be due, for example,to political decisions or historical events. Tominimise costs, the sellers will use the euro asthe invoicing currency for crude oil if

C (e) < C (d )

Therefore, the probability – p t – that a seller will invoice a crude oil contract in euro at timet is as follows:

pt = Pr { C (e) < C (d ) }

= Pr {(1 – ˆ p t + 1) [τ + i(p t )] + ˆ p t + 1 i(p t ) +εe

t < ˆ p t + 1 τ + εd t }

= Pr { ε et – ε d

t < 2 ˆ p t + 1 τ – τ – i(p t )}.

Assuming that εd and εe are independently andidentically distributed across sellers accordingto the extreme value distribution, the difference,ε e

t – εd t , is approximately logistically distr ibuted.

Therefore, the best response function is

pt = β ( pt )]}2 ˆ pt + 1 τ τ + exp 11 { [ ─ ─ ─ i ,

Ta le 2 Cost atrix

B(d) B(e)

S(d) τ S(e) τ + i(p t ) i(p t )



17ECB




in which β is a parameter indicating the weightof the deterministic variables. Assumingrational expectations, the expected share of imports of food invoiced in euro at time t + 1is ˆ p t + 1 . While no closed-form solution to theabove equation can be found, the next sectionuses simulation to analyse the steady states anddynamics of the model.

4.3 STEAdY STATES ANd THE AdOPTION CURVE

Figure 2 plots the graph of the best responsefunction using hypothetical values between0.0004 and 0.20 for transaction costs. The valueτ = 0.0004 is the actual average of the monthly

bid-ask spreads as a percentage of the mid-priceas reported by Bloomberg for the periodJanuary 1999-July 2005. Information costs – i(p t ) – are given a value of 0.20 when the marketshare of the euro in invoicing is pt = 0 , and i(p t ) approaches zero when the currency shares areequal, i.e. p t approaches 0.50 .15 Here it is assumed

that β = 20 (or, alternatively, the dominance of the stochastic term, ε et – ε d

t , is 0.05 ).

When transaction costs are high ( 0.15 and0.20 ), the model predicts multiple steadystates within the interval [0; 1]. There are twostable equilibria – low at p t = 0 and high where

p t is close to 1. The equilibrium at p t = 0.50 isunstable. Therefore, when transaction costs arevery high, parallel use of both currencies is nota stable equilibrium. Unless the majority of oilexporters switch simultaneously to invoicing ineuro, the US dollar will remain the dominantcurrency in the market. In a more realisticenvironment of very low transaction costs,however, there is one stable equilibrium at around

pt

= 0.50 . Thus, with the assumptions made inorder to plot Chart 2 and with low transactioncosts, the market should move towards the use of

both currencies in oil invoicing once a thresholdlevel of around 10% of the market switches tothe use of the euro. The next section relaxes theassumptions regarding non-network effects andinformation costs and analyses the impact of thesize of β and i(p t ) on the model dynamics.

4.4 SENSITIVITY ANALYSIS FOR THE mOdELPARAmETERS

The preceding analysis shows that even if anoil exporter expects all imports to be pricedin euro and, at the same time, transaction costs

In this sample illustration of the model, the information cost15function used is i(p t ) = 0.20 exp(-7 p t ). The exponential decayform is a proxy for information costs, which decrease as thesize of the market increases.

Chart 2 mo el yna ics for varioustransaction costs

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

45-degree Line

0 0.2 0.4 0.6 0.8 1

τ = 0.0004 τ = 0.10 τ = 0.05 τ = 0.15

τ = 0.20

y-axis:x-axis: ˆ pt + 1

t p

Sources: Bloomberg (2005) and authors’ calculations. Note: β = 20; i(p t ) = 0.20 exp(-7 p t ).

Chart 3 mo el yna ics for various valuesof β

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

0 0.2 0.4 0.6 0.8 1

β = 10β = 20β = 100

β = 1,00045-degree line

β = 0

px-axis:y-axis:

ˆ pt + 1

t

Sources: Bloomberg (2005) and authors’ calculations. Note: τ = 0.0004; i(p t ) = 0.20 exp(-7 p t ).




are very low, its best response is to invoice itsexport contracts in euro with a probability of less than one. This is for two reasons. First,it has to learn, over time, how to compare oil

prices in euro, i.e. its choice depends on the sizeand speed of decline of the information costsi(p t ). Second, the possibility exists thatstochastic, external shocks will reduce thelikelihood of all oil contracts being invoicedin euro. The importance of stochastic shocksis measured by the size of β . Hence, theassumptions made about the parameter β andthe information costs warrant further discussionof the behaviour of the best response function.

Chart 3 plots the best response functionassuming the same information costs as beforeand low transaction costs ( τ = 0.0004 ), butvarying the magnitude of β . For the extremevalue of β = 0 , which is equivalent to an in nitein uence of the stochastic term, the playerschoose their response as if ipping a coin, and

so p t = 0.50 . For the higher values of β = 10 and β = 20 , there is a unique stable equilibrium ataround p t = 0.50 . These results are consistentwith a case in which non-network effects’speci c costs have a considerable in uenceon the players’ decision-making process (5%or above). In the other extreme, non-network effects have minimal impact ( β = 100 and

β = 1,000 ) and the players choose the oilinvoicing currency mainly on the basis of economic considerations. Hence, very smalltransaction costs by comparison with theinformation costs preclude any switch awayfrom the vehicle currency; the only stableequilibrium is at p t = 0 . The oil exporters prefer to use the US dollar as a vehicle currency andexchange it for euro when purchasing imports.

When transaction costs are non-trivial, 16 however,the best response function approximates a stepfunction for large values of β (see Chart 4).Given the costs of invoicing in a particular currency, the players choose to invoice in euroif network effects work to their advantage, i.e.the correctly expected share of oil invoicing ineuro is 0.50 or above.

Chart 5 shows the behaviour of the bestresponse function with information costs of thesame functional form, but starting at various

values of i(p t ) for p t = 0 . Lower informationcosts result in faster convergence toward thestable equilibrium at p t = 0.50 . More exporters

With these assumptions, the best response function16approximates a step function when transaction costs aregreater than 40 basis points. The lower the transaction costs,the higher the value of ˆ p

t + 1 , at which the oil exporters switchto euro.

Chart 4 mo el yna ics for various valuesof β an high transaction costs

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

45-degree Line

β = 0β = 20

β = 100β = 10

β = 1,000

0 0.2 0.4 0.6 0.8 1

pt x-axis:y-axis: ˆ pt + 1

Source: Authors’ calculations. Note: τ = 0.03; i(p t ) = 0.20 exp(-7 p t ).

Chart 5 mo el yna ics for variousinfor ation costs

0.0

0.2

0.4

0.6

0.8

1.0

0.0

0.2

0.4

0.6

0.8

1.0

0 0.2 0.4 0.6 0.8 1

A = 0.05

A = 0.10

45-degree Line

A = 0.20

A = 0.30

A = 0.40

pt x-axis:y-axis: ˆ pt + 1

Source: Authors’ calculations. Note: τ = 0.0004; β = 20.



19ECB




invoice in euro if price transparency of euro-invoiced contracts is higher. Developments suchas the new euro pricing of contracts by Plattsor a commodity exchange quoting oil contractsin euro may contribute to the establishment of such a situation.

Our simulation results con rm the predictionsof the network effects theory regardingthe existence of multiple equilibria and theimportant role of critical mass. In particular, astable equilibrium of parallel oil invoicing in twocurrencies can arise if: (a) non-network-relatedcosts, such as political or social considerations,have a moderate impact on the players’decisions; (b) transaction costs are small;(c) a certain threshold share of euro invoicing isexpected; and, nally, (d) information costs areeither low or decline quickly with increasinguse of the euro. According to our model, oneexplanation of the current state of the crude oilmarket (i.e. US dollar domination and very low

transaction costs) may be very high informationcosts coupled with very low impact of speci cnon-network effects. When players’ decisionsare based mainly on the economic costs of the choice of invoicing currency, they prefer to pay the low transaction costs of exchangingcurrencies or hedging against a currency risk rather than incur the costs associated withinformation transparency. A second possibilityis that no players rationally expect that thethreshold level of euro invoicing will be reachedin the forthcoming period.




5 CONCLUSION

The theoretical literature on trade invoicingexplains the almost universal use of theUS dollar in international trade in crudeoil by means of the fact that petroleum isa homogeneous good traded in organisedexchanges. Apart from serving as a medium of exchange, the US dollar ful ls the function of aunit of account by providing price t ransparencyin the oil market. Thirdly, the macroeconomicstability of the United States and the depth of theUS nancial markets explain the role of the USdollar as a store of value and the low liquiditycosts associated with holding the currency.

The literature makes a strong case for the useof one currency as a vehicle currency in theoil trade. However, a thorough review of theinternational market for crude oil points toseveral factors suggesting that the oil marketis less homogeneous and global as commonly

perceived, which indicates that invoicing in onecurrency may not be the only solution. A groupof 11 developing countries highly dependent on

petroleum exports dominates the internationaloil trade. The out ow of crude oil from mostexporting countries is matched by an in owof other goods and services from their trading

partners – usually nearby developed countries.Similarly, the United States, the biggestimporter of petroleum, relies mainly on westernhemisphere sources. Thus, owing mainly to thespeci c features of the industry, the internationaloil trade is predominantly regional in nature. Inaddition, the introduction of trading in futurescontracts for petroleum grades more relevant tolocal industry, with such contracts denominatedin domestic currencies and traded in nancialcentres other than New York and London, hascontributed further to the segmentation of thecrude oil market.

To explain the dominant use of the US dollar inoil invoicing, the model developed in this paper treats currencies as network goods. Sellers inthe market respond to the currency choices of

buyers so as to minimise costs associated withthe use of an established vehicle currency or a

newly introduced currency. The model explainsthe possibility of multiple equilibria with one or two vehicle currencies.

When calibrated using actual values for thetransaction costs of using US and/or eurodollars, together with a proxy for informationcosts, which decline as use of the new currencyincreases, the model identi es the preconditionsfor a possible switch to parallel invoicing: a)

players have to expect that a certain minimumnumber of other players will also start usingthe new currency, or b) the information costsassociated with quoting oil contracts in twocurrencies are low.



21ECB


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APPENdIX

WORLd CRUdE OIL TR AdE FLOWSTa le 1 Worl exports of cru e oil, 2003

Ranking Country Thousand barrels per day Percentage of total

1 Saudi Arabia* 6,522.9 16.28%2 Former USSR 6,479.5 16.17%3 Norway 2,694.2 6.72%4 Iran* 2,396.3 5.98%

5 Nigeria* 2,303.5 5.75%

6 Mexico 2,102.9 5.25%7 United Arab Emirates* 2,048.0 5.11%8 Canada 1,553.6 3.88%

9 Venezuela* 1,535.0 3.83%10 United Kingdom 1,345.4 3.36%

11 Kuwait* 1,242.9 3.10%12 Libya* 1,126.5 2.81%13 Oman 901.9 2.25%14 Algeria* 741.0 1.85%

15 Angola 698.2 1.74%

16 Indonesia* 650.2 1.62%17 Columbia 564.1 1.41%18 Qatar* 540.7 1.35%19 Malaysia 397.9 0.99%

20 Iraq* 388.6 0.97%

21 Syria 335.9 0.84%22 Gabon 312.7 0.78%23 Vietnam 302.3 0.75%24 Australia 282.1 0.70%

25 Congo 253.5 0.63%26 Ecuador 238.2 0.59%27 Brunei 177.1 0.44%28 China 163.1 0.41%29 Cameroon 120.7 0.30%

30 Trinidad and Tobago 60.2 0.15%

31 Egypt 56.4 0.14%32 United States 22.1 0.06%

TOTAL WORLD 40,065.8 100.00%OPEC 19,495.7 48.66%

Source: OPEC Annual Statistical Bulletin, 2003.*OPEC members; Angola joined OPEC only in 2007.



25ECB


APPENdIX

Ta le 2 Worl I ports of Cru e Oil , 2003

Ranking Country Thousand barrels per day Percentage of total

1 United States 10,348.8 25.56%2 Japan 4,162.7 10.28%3 South Korea 2,166.1 5.35%4 Germany 2,138.8 5.28%

5 China* 1,829.5 4.52%

6 France 1,708.0 4.22%7 Italy 1,686.3 4.16%8 India 1,574.1 3.89%

9 Spain 1,150.7 2.84%10 Netherlands 974.5 2.41%

11 United Kingdom 967.6 2.39%12 Canada 888.9 2.20%13 Singapore 823.0 2.03%14 Taiwan 768.7 1.90%

15 Belgium 727.9 1.80%

16 Thailand 686.1 1.69%17 Turkey 483.9 1.19%18 Virgin Islands 443.6 1.10%19 Brazil 419.7 1.04%

20 Sweden 406.1 1.00%

21 Greece 397.3 0.98%22 Australia 377.9 0.93%23 Indonesia 306.7 0.76%24 Philippines 306.3 0.76%

25 Bahrain 225.0 0.56%26 Netherlands Antilles 222.0 0.55%27 Chile 195.2 0.48%28 Morocco 145.2 0.36%29 Romania 140.0 0.35%

30 Czech Republic 128.8 0.32%

31 Puerto Rico 123.9 0.31%32 Bulgaria 115.8 0.29%33 New Zealand 95.6 0.24%34 Cote d'Ivoire 72.4 0.18%

35 Former USSR 40.0 0.10%

36 Kenya 36.3 0.09%37 Cuba 14.5 0.04%

TOTAL WORLD 40,494.4 100.00%

Source: OPEC Annual Statistical Bulletin, 2003*Crude oil gure from BP 2004, because OPEC 2003 includes it under 'Asia and Paci c - Others".




Ta le 3 US cru e oil i ports y countr y of origin, 2004

Country Thousand barrels per day Percentage of total

Arab OPEC 2,634 26.11%Algeria 215 2.13%Iraq 655 6.49%Kuwait 241 2.39%Libya 18 0.18%Qatar 4 0.04%Saudi Arabia 1,495 14.82%United Arab Emirates 5 0.05%

Other OPEC 2,408 23.87%

Indonesia 34 0.34% Nigeria 1,078 10.69%Venezuela 1,297 12.86%

Non-OPEC 5,046 50.02%

Angola 306 3.03%Canada 1,616 16.02%Colombia 142 1.41%Ecuador 232 2.30%Gabon 142 1.41%Mexico 1,598 15.84%

Norway 143 1.42%Russia 158 1.57%United Kingdom 238 2.36%Other 467 4.63%

TOTAL 10,088 100.00%

Source: Energy Information Administration, June 2005 ; Petroleum Supply Annual, Volume I, 2004. Note: Angola joined OPEC only in 2007



27ECB


EUROPEANCENTRAL bANK

OCCASIONALPAPER SERIES

EUROPEAN CENTRAL bANKOCCASIONAL PAPER SERIES

1 “The impact of the euro on money and bond markets” by J. Santillán, M. Bayle and C. Thygesen,July 2000.

2 “The effective exchange rates of the euro” by L. Buldorini, S. Makrydakis and C. Thimann,February 2002.

3 “Estimating the trend of M3 income velocity underlying the reference value for monetarygrowth” by C. Brand, D. Gerdesmeier and B. Rof a, May 2002.

4 “Labour force developments in the euro area since the 1980s” by V. Genre andR. Gómez-Salvador, July 2002.

5 “The evolution of clearing and central counterpar ty services for exchange-traded derivatives inthe United States and Europe: a comparison” by D. Russo, T. L. Hart and A. Schönenberger,September 2002.

6 “Banking integration in the euro area” by I. Cabral, F. Dierick and J. Vesala, December 2002.

7 “Economic relations with regions neighbouring the euro area in the ‘Euro Time Zone’”

by F. Mazzaferro, A. Mehl, M. Sturm, C. Thimann and A. Winkler, December 2002.

8 “An introduction to the ECB’s survey of professional forecasters” by J. A. Garcia,September 2003.

9 “Fiscal adjustment in 1991-2002: stylised facts and policy implications” by M. G. Briotti,February 2004.

10 “The acceding countries’ strategies towards ERM II and the adoption of the euro: ananalytical review” by a staff team led by P. Backé and C. Thimann and including O. Arratibel,O. Calvo-Gonzalez, A. Mehl and C. Nerlich, February 2004.

11 “Of cial dollarisation/euroisation: motives, features and policy implications of current cases” by A. Winkler, F. Mazzaferro, C. Nerlich and C. Thimann, February 2004.

12 “Understanding the impact of the external dimension on the euro area: trade, capital owsand other international macroeconomic linkages“ by R. Ander ton, F. di Mauro and F. Moneta,March 2004.

13 “Fair value accounting and nancial stability” by a staff team led by A. Enria and includingL. Cappiello, F. Dierick, S. Grittini, A. Maddaloni, P. Molitor, F. Pires and P. Poloni,April 2004.

14 “Measuring nancial integration in the euro area” by L. Baele, A. Ferrando, P. Hördahl, E. Krylova, C. Monnet, April 2004.




15 “Quality adjustment of European price statistics and the role for hedonics” by H. Ahnert and G. Kenny, May 2004.

16 “Market dynamics associated with credit ratings: a literature review” by F. Gonzalez, F. Haas,R. Johannes, M. Persson, L. Toledo, R. Violi, M. Wieland and C. Zins, June 2004.

17 “Corporate ‘excesses’ and nancial market dynamics” by A. Maddaloni and D. Pain, July 2004.

18 “The international role of the euro: evidence from bonds issued by non-euro area residents” by A. Geis, A. Mehl and S. Wredenborg, July 2004.

19 “Sectoral specialisation in the EU: a macroeconomic perspective” by MPC task force of theESCB, July 2004.

20 “The supervision of mixed nancial services groups in Europe” by F. Dierick, August 2004.

21 “Governance of securities clearing and settlement systems” by D. Russo, T. Hart,M. C. Malaguti and C. Papathanassiou, October 2004.

22 “Assessing potential output growth in the euro area: a growth accounting perspective”

by A. Musso and T. Westermann, January 2005.

23 “The bank lending survey for the euro area” by J. Berg, A. van Rixtel, A. Ferrando, G. de Bondtand S. Scopel, February 2005.

24 “Wage diversity in the euro area: an overview of labour cost differentials across industries” by V. Genre, D. Momferatou and G. Mourre, February 2005.

25 “Government debt management in the euro area: recent theoretical developments and changesin practices” by G. Wolswijk and J. de Haan, March 2005.

26 “The analysis of banking sector health using macro-prudential indicators” by L. Mörttinen,P. Poloni, P. Sandars and J. Vesala, March 2005.

27 “The EU budget – how much scope for institutional reform?” by H. Enderlein, J. Lindner,O. Calvo-Gonzalez, R. Ritter, April 2005.

28 “Reforms in selected EU network industries” by R. Martin, M. Roma, I. Vansteenkiste,April 2005.

29 “Wealth and asset price effects on economic activity”, by F. Altissimo, E. Georgiou, T. Sastre,M. T. Valderrama, G. Sterne, M. Stocker, M. Weth, K. Whelan, A. Willman, June 2005.

30 “Competitiveness and the export performance of the euro area”, by a Task Force of the MonetaryPolicy Committee of the European System of Central Banks, June 2005.



29ECB




31 “Regional monetary integration in the member states of the Gulf Cooperation Council (GCC)” by M. Sturm and N. Siegfried, June 2005.

32 “Managing nancial crises in emerging market economies: experience with the involvement of private sector creditors” by an International Relations Committee task force, July 2005.

33 “Integration of securities market infrastructures in the euro area” by H. Schmiedel,A. Schönenberger, July 2005.

34 “Hedge funds and their implications for nancial stability” by T. Garbaravicius and F. Dierick,August 2005.

35 “The institutional framework for nancial market policy in the USA seen from an EU perspective” by R. Petschnigg, September 2005.

36 “Economic and monetary integration of the new Member States: helping to chart the route” by J. Angeloni, M. Flad and F. P. Mongelli, September 2005.

37 “Financing conditions in the euro area” by L. Bê Duc, G. de Bondt, A. Calza,D. Marqués Ibáñez, A. van Rixtel and S. Scopel, September 2005.

38 “Economic reactions to public nance consolidation: a survey of the literature” by M. G. Briotti,

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39 “Labour productivity in the Nordic EU countries: a comparative overview and explanatoryfactors – 1998-2004” by A. Annenkov and C. Madaschi, October 2005.

40 “What does European institutional integration tell us about trade integration?” by F. P. Mongelli,E. Dorrucci and I. Agur, December 2005.

41 “Trends and patterns in working time across euro area countries 1970-2004: causesand consequences” by N. Leiner-Killinger, C. Madaschi and M. Ward-Warmedinger,December 2005.

42 “The New Basel Capital Framework and its implementation in the European Union” by F. Dierick, F. Pires, M. Scheicher and K. G. Spitzer, December 2005.

43 “The accumulation of foreign reserves” by an International Relations Committee Task Force,February 2006.

44 “Competition, productivity and prices in the euro area services sector” by a Task Force of theMonetary Policy Committee of the European System of Central banks, April 2006.

45 “Output growth differentials across the euro area countr ies: Some stylised facts” by N. Benalal,J. L. Diaz del Hoyo, B. Pierluigi and N. Vidalis, May 2006.

46 “In ation persistence and price-setting behaviour in the euro area – a summary of the IPN

evidence”, by F. Altissimo, M. Ehrmann and F. Smets, June 2006.




47 “The reform and implementation of the stability and growth pact” by R. Morris, H. Ongena andL. Schuknecht, June 2006.

48 “Macroeconomic and nancial stability challenges for acceding and candidate countries” by the International Relations Committee Task Force on Enlargement, July 2006.

49 “Credit risk mitigation in central bank operations and its effects on nancial markets: the caseof the Eurosystem” by U. Bindseil and F. Papadia, August 2006.

50 “Implications for liquidity from innovation and transparency in the European corporate bondmarket” by M. Laganá, M. Perina, I. von Köppen-Mertes and A. Persaud, August 2006.

51 “Macroeconomic implications of demographic developments in the euro area” by A. Maddaloni,A. Musso, P. Rother, M. Ward-Warmedinger and T. Westermann, August 2006.

52 “Cross-border labour mobility within an enlarged EU” by F. F. Heinz and M. Ward-Warmedinger,October 2006.

53 “Labour productivity developments in the euro area” by R. Gomez-Salvador, A. Musso,M. Stocker and J. Turunen, October 2006.

54 “Quantitative quality indicators for statistics – an application to euro area balance of payment

statistics” by V. Damia and C. Picón Aguilar, November 2006

55 “Globalisation and euro area trade: Interactions and challenges” by U. Baumann andF. di Mauro, February 2007.

56 “Assessing scal soundness: Theory and practice” by N. Giammarioli, C. Nickel, P. Rother,J.-P. Vidal, March 2007.

57 “Understanding price developments and consumer price indices in south-eastern Europe” by S. Herrmann and E. K. Polgar, March 2007.

58 “Long-Term Growth Prospects for the Russian Economy” by R. Beck, A. Kamps and E. Mileva,March 2007.

59 “The ECB Survey of Professional Forecasters (SPF) a review after eight years’ experience”, by C. Bowles, R. Friz, V. Genre, G. Kenny, A. Meyler and T. Rautanen, April 2007.

60 “Commodity price uctuations and their impact on monetary and scal policies in Western andCentral Africa” by U. Böwer, A. Geis and A. Winkler, April 2007.

61 “Determinants of growth in the central and eastern European EU Member States – A productionfunction approach” by O. Arratibel, F. Heinz, R. Martin, M. Przybyla, L. Rawdanowicz,R. Sera ni and T. Zumer, April 2007.

62 “In ation-linked bonds from a Central Bank perspective” by J. A. Garcia and A. van Rixtel,

June 2007.



31ECB




63 “Corporate nance in the euro area – including background material”, Task Force of theMonetary Policy Committee of the European System of Central Banks, June 2007.

64 “The use of portfolio credit risk models in central banks”, Task Force of the Market OperationsCommittee of the European System of Central Banks, July 2007.

65 “The performance of credit rating systems in the assessment of collateral used in Eurosystemmonetary policy operations” by F. Coppens, F. González and G. Winkler, July 2007.

66 “Structural reforms in EMU and the role of monetary policy – a survey of the literature” by N. Leiner-Killinger, V. López Pérez, R. Stiegert and G. Vitale, July 2007.

67 “Towards harmonised balance of payments and international investment position statistics – theexperience of the European compilers” by J.-M. Israël and C. Sánchez Muñoz, July 2007.

68 “The securities custody industry” by D. Chan, F. Fontan, S. Rosati and D. Russo, August 2007.

69 “Fiscal policy in Mediterranean countries – Developments, structures and implications for monetary policy” by M. Sturm and F. Gurtner, August 2007.

70 The search for Columbus’ egg: Finding a new formula to determine quotas at the IMF by M. Skala, C. Thimann and R. Wöl nger, August 2007.

71 “The economic impact of the Single Euro Payments Area” by H. Schmiedel, August 2007.

72 “The role of nancial markets and innovation in productivity and growth in Europe” by P. Hartmann, F. Heider, E. Papaioannou and M. Lo Duca, September 2007.

73 “Reserve accumulation: objective or by-product?” by J. O. de Beaufort Wijnholds andLars Søndergaard, September 2007.

74 “Analysis of revisions to general economic statistics” by H. C. Dieden and A. Kanutin,October 2007.

75 “The role of other nancial intermediaries in monetary and credit developments in the euro area”edited by P. Moutot and coordinated by D. Gerdesmeier, A. Lojschová and J. von Landesberger,October 2007.

76 “Prudential and oversight requirements for securities settlement a comparison of cpss-iosco” byD. Russo, G. Caviglia, C. Papathanassiou and S. Rosati, November 2007

77 “Oil market structure, network effects and the choice of currency for oil invoicing” by E. Mileva and N. Siegfried, November 2007.

ecb paper - oil, currency

Documents